4 research outputs found

    Real Language Users

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    The idea of a perfectly competent but resource limited language user is the basis of many models of sentence comprehension. It is widely assumed that linguistic competence is a) uniform; b) generative; c) autonomous; d) automatic and e) constant. It is also believed that the free expression of these properties is frustrated by limits in the availability of computational resources. However, no firm experimental evidence for the classical language user appears to exist. Negative evidence for each assumption is reviewed here and the notion of resource limitations is shown to be suspect. An experiment is reported which tested each of the five assumptions underlying the conventional notion of linguistic competence. It was found that native speakers of English a) differed in grammatical skill; b) often failed to display productivity; c) violated syntax in favour of plausibility; d) expended conscious effort to comprehend some sentences and e) appeared to adapt to novel structures as the experiment progressed. In line with previous studies, a relationship was found between comprehension skill and formal education. A new finding is that highly educated non-native speakers of English can outperform less educated native speakers of English in comprehending grammatically challenging English sentences. The results indicate that the classical language user is an inaccurate model of real language users, who appear to differ considerably in linguistic skill. A number of specific questions for further research are raised

    The role of terminology and local grammar in video annotation

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    The linguistic annotation' of video sequences is an intellectually challenging task involving the investigation of how images and words are linked .together, a task that is ultimately financially rewarding in that the eventual automatic retrieval of video (sequences) can be much less time consuming, subjective and expensive than when retrieved manually. Much effort has been focused on automatic or semi-automatic annotation. Computational linguistic methods of video annotation rely on collections of collateral text in the form of keywords and proper nouns. Keywords are often used in a particular order indicating an identifiable pattern which is often limited and can subsequently be used to annotate the portion of a video where such a pattern occurred. Once' the relevant keywords and patterns have been stored, they can then be used to annotate the remainder of the video, excluding all collateral text which does not match the keywords or patterns. A new method of video annotation is presented in this thesis. The method facilitates a) annotation extraction of specialist terms within a corpus of collateral text; b) annotation identification of frequently used linguistic patterns to use in repeating key events within the data-set. The use of the method has led to the development of a system that can automatically assign key words and key patterns to a number of frames that are found in the commentary text approximately contemporaneous to the selected number of frames. The system does not perform video analysis; it only analyses the collateral text. The method is based on corpus linguistics and is mainly frequency based - frequency of occurrence of a key word or key pattern is taken as the basis of its representation. No assumptions are made about the grammatical structure of the language used in the collateral text, neither is a lexica of key words refined. Our system has been designed to annotate videos of football matches in English a!ld Arabic, and also cricket videos in English. The system has also been designed to retrieve annotated clips. The system not only provides a simple search method for annotated clips retrieval, it also provides complex, more advanced search methods.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
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